A new Volterra predistorter based on the indirect learningarchitecture
IEEE Transactions on Signal Processing
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Polynomial pre-distortion techniques for power amplifier (PA) non-linearity based on indirect learning architecture (IDLA) are widely used. The benefit of the IDLA leaves unnecessary the assumption of a model for PA, corresponding parameters estimation and inverse construction. In this paper, a novel scheme based on IDLA for PA pre-distortion is proposed. It has better power spectral density (PSD) and relative mean square error (RMSE) performances than the conventional IDLA-based methods especially when the PA non-linearity is more severe. Simulations and theoretical analysis verify the good performances of the proposed scheme.